The Application of Motion Trajectory Acquisition and Intelligent Analysis Technology in Physical Education Teaching in Colleges and Universities

Author:

Wang Yun12ORCID,Han Yong2,Wang Qiang2

Affiliation:

1. Beijing Sport University, Beijing100084, China

2. Xichang University, Xichang 615000, Sichuan, China

Abstract

Traditional classroom teaching analysis is mainly based on manual coding of time sampling, which has problems such as overreliance on experts, low analysis efficiency, and difficulty in large-scale services. Classroom teaching analysis based on artificial intelligence technology breaks through the predicament. With the continuous development of intelligent analysis technology, the research on physical education in colleges and universities becomes more and more meaningful. The task of physical education is to impart physical knowledge, technology, and skills to students, enhance their physical fitness, and cultivate their morality, will, and quality. It is one of the ways to implement sports goals. This article proposes how to change traditional teaching based on intelligent analysis technology. This article aims to study how to apply the emerging intelligent analysis technology to the physical education teaching process in colleges and universities; this enables students to be more personalized in the learning process, stimulates their enthusiasm for learning, and meets their basic requirements, breaking through traditional teaching methods, and making it possible to teach students in accordance with their aptitude. In the experimental analysis of this article, from the overall trend of the student evaluation data for 7 consecutive semesters, it can be found that the minimum value of the mean, median, and mode appears in the first semester of the 2016–2017 school year, and the maximum appears in the first semester of the 2019–2020 school year. The average score (mean) of students' evaluation of teaching fluctuates from 4.71 to 4.72, and the fluctuating range of the students' evaluation score (median) of the middlemost students is from 4.56 to 4.66. The results show that the intelligent analysis technology has played a stimulating effect on teachers' teaching and effectively mobilized teachers' teaching initiative. Therefore, the application of intelligent analysis technology is very necessary. Combine health education with moral education, intellectual education, physical education, aesthetic education, and labor education, and integrate it into the whole process of education, teaching, management and services, and build a health education system that is oriented to and responsible for everyone.

Funder

National People's Congress

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Information Systems

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